metadata

license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: spa-eng-pos-tagging-v6
    results: []

spa-eng-pos-tagging-v6

This model is a fine-tuned version of distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.3128
Accuracy: 0.9056
Precision: 0.9032
Recall: 0.8293
F1: 0.8345
Hamming Loss: 0.0944

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 14

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Hamming Loss
1.0141	1.0	1744	0.7804	0.7158	0.7328	0.6183	0.6345	0.2842
0.6292	2.0	3488	0.5384	0.7973	0.8111	0.7029	0.7213	0.2027
0.4438	3.0	5232	0.4236	0.8462	0.8346	0.7762	0.7732	0.1538
0.3626	4.0	6976	0.3856	0.8651	0.8524	0.7933	0.7903	0.1349
0.3141	5.0	8720	0.3697	0.8712	0.8688	0.7998	0.8028	0.1288
0.2575	6.0	10464	0.3689	0.8751	0.8758	0.8003	0.8058	0.1249
0.2117	7.0	12208	0.3329	0.8890	0.8832	0.8169	0.8184	0.1110
0.1864	8.0	13952	0.3235	0.9010	0.8946	0.8278	0.8293	0.0990
0.1555	9.0	15696	0.3128	0.9056	0.9032	0.8293	0.8345	0.0944
0.1322	10.0	17440	0.3311	0.9088	0.9010	0.8376	0.8377	0.0912
0.1111	11.0	19184	0.3394	0.9101	0.9081	0.8319	0.8383	0.0899
0.0874	12.0	20928	0.3472	0.9148	0.9100	0.8407	0.8440	0.0852
0.0659	13.0	22672	0.3635	0.9131	0.9072	0.8400	0.8422	0.0869
0.0608	14.0	24416	0.3560	0.9187	0.9140	0.8452	0.8482	0.0813

Framework versions

Transformers 4.32.0
Pytorch 2.0.1+cu118
Tokenizers 0.13.3